The default AI playbook is "buy everyone a Copilot licence and hope productivity lifts." That's a
procurement decision, not a transformation. OMX takes the opposite path — start with the value stream,
find the friction and noise, then design a small, repeatable, governed agent that removes it.
Same data. Same people. Less drag.
Every staff member gets a Copilot / Claude / chat tool. Adoption is uneven. Output quality is uneven. Governance is unclear. Sensitive data leaks via opportunistic copy-paste. The bill compounds; the value doesn't.
The OMX pattern
Value-stream augmentation
Map the value stream. Pin the highest-friction step. Build a governed agent for that step — role-aware, business-aware, live-data-fed. Roll out the process, not the licence. Measure the friction removed, not the seats sold.
2 · The model
Five moves, in order. Skip one and the system falls back to seat-licence sprawl.
01 IDENTIFY
Map the value stream
Pick one stream end-to-end. Quote -> cart -> invoice. Lead -> opp -> close.
02 LOCATE
Pin the friction
Where does work wait? Where is data re-entered? Where does someone email a screenshot?
03 ENCODE
Repeatable process
Same inputs, same outputs, every time. If it's not repeatable yet, it's not ready for an agent.
04 AUGMENT
Governed agent
Role context + business knowledge + live data. Auditable, reversible, scoped to one job.
05 MEASURE
Friction removed
Cycle time before vs after. Error rate. Cost per transaction. The stream's own KPIs, not licence counts.
What every agent must carry
Secure
Identity bound to the person and role. Tenant-scoped. No shared service accounts. PII on the same rails as everything else.
Governed
Versioned prompts, change control, audit logs. Every output traceable to inputs. Approval gates where action is material.
Controlled
Bounded scope — does one job. Cannot do other people's jobs. Cannot escalate. Fails closed.
Locked CLAUDE.md
Every agent runs against a managed, version-pinned CLAUDE.md — rules, hard constraints, business glossary. The agent's behaviour is config, not improvisation.
CrowdStrike on endpoint
Same endpoint-protection layer the rest of OMX runs on. Agent activity is visible to the SOC. No off-fleet machines, no shadow installs.
Role context
Knows who is asking, what they're allowed to see, what their team owns, what the next step looks like for them.
Augment: matching agent finds OMX equivalents from competitor SKU lists; sustainability scoring; switches the cart.
5 · The AI SDLC — what we've already built
The Pathway isn't theory. The same pattern that augments the value stream also augments our software lifecycle —
Claude in the loop on every spec, every build, every review. The platforms below were all delivered through this
AI-augmented SDLC: small focused agents, locked CLAUDE.md per project, governed by the same spine on the diagram above.
Lens
OMX BI platform on Snowflake
In production. Replaces Sisense ($130k/yr reclaim from January). Same data, better UX. The classifier-grade proof of fit-for-OMX over packaged SaaS.
Accelerate
EPMO portfolio app — the PMO is the demo
Live PMO at accelerate.officemax.co.nz. Tier-aware governance, RAG, RASCI, milestones, status. The PMO process is now the codebase. ~$30k/yr packaged-PM reclaim.
WhoOnSite
NFC + Gallagher frontline identity
In production. AD-only workers without SF licences finally have a system-of-presence. Input to DC Optimisation, Mobile Workforce, Desk Booking.
Ribbons (IT Help Desk Discovery)
File-move mechanic + operational sequence
AI-led discovery of the IT Help Desk intake process; ribbons design, operational sequencing, technical lead clarified. Feeds the AWS Connect IT Help Desk migration.
Stage 1 Diagnose
Servicing the Unmanaged — programme diagnosis
AI-assisted diagnosis of the unmanaged-540k opportunity. The base layer underneath the six-stage roadmap (Diagnose → Web Opt → Switching → Reorder → Marketplace → The Ball).
Briefing Room + 183 Deep Dives
Company Research engine
Front-end + QBR process + 183 strategy dives on big NZ companies, all built in the AI SDLC. The augmented account-research stream proven in code.
Plex-CI scraper
Competitor intelligence sitemap engine
Sitemap channel unblocked 2026-06-27: 545,789 URLs and 471,991 change events across 59 competitors. Built in days, not months, through AI-paired implementation.
JARVIS + 181-agent harness
The internal AI control plane
3-layer agent architecture (Router → 14 Supervisors → 163 Specialists). The framework that orchestrates the SDLC we're describing. Eating our own cooking.
The point: none of this required a transformation programme to start. Each platform was a small focused build by a small focused team with AI in the loop — same pattern as the value-stream agents we're proposing for the next wave.
6 · The detailed stories
Each link below opens the deep narrative for a programme already in the AI Pathway shape — value stream identified, friction named, governed agent designed or shipping. Walk any one to see the pattern in real OMX context.